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Record W4396655697 · doi:10.1080/02699052.2024.2347548

Implementation of the strengths model of case management for people with a traumatic brain injury: a qualitative pre-implementation study

2024· article· en· W4396655697 on OpenAlexafffund
Pascale Simard, Samuel Turcotte, Catherine Vallée, Marie‐Ève Lamontagne

Bibliographic record

VenueBrain Injury · 2024
Typearticle
Languageen
FieldHealth Professions
TopicHealth Policy Implementation Science
Canadian institutionsUniversité LavalCentre for Interdisciplinary Research in Rehabilitation
FundersCanadian Institutes of Health Research
KeywordsTraumatic brain injuryCommunity integrationIntervention (counseling)Acquired brain injuryCognitionPsychologyMental healthPopulationPhysical medicine and rehabilitationMedicineClinical psychologyPsychiatryRehabilitationPhysical therapyEnvironmental health

Abstract

fetched live from OpenAlex

INTRODUCTION: People who sustain a traumatic brain injury (TBI) may have to live with permanent sequelae such as mental health problems, cognitive impairments, and poor social participation. The strengths-based approach (SBA) of case management has a number of positive impacts such as greater community integration but it has never been implemented for persons with TBI. To support its successful implementation with this population, it is essential to gain understanding of how the key components of the intervention are perceived within the organization applying the approach. OBJECTIVES: Documenting the barriers and facilitators in the implementation of the SBA as perceived by potential adopters. METHODS: A qualitative pre-implementation study was conducted using semi-structured interviews with community workers and managers of the community organization where the SBA is to be implemented. Data were analyzed using a deductive approach based on the Consolidated Framework for Implementation Research (CFIR). RESULTS: The major barriers are associated with the intervention (e.g. adaptability of the intervention) and the external context (e.g. the impact of the pandemic). Perceived facilitators are mainly associated with the internal context (e.g. compatibility with current values). CONCLUSION: The barriers and facilitators identified will inform the research team's actions to maximize the likelihood of successful implementation.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.005
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.070
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.341
GPT teacher head0.671
Teacher spread0.331 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2024
Admission routes2
Has abstractyes

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